tf.keras.ops.normalize
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Normalizes x over the specified axis.
tf.keras.ops.normalize(
x, axis=-1, order=2
)
It is defined as: normalize(x) = x / max(norm(x), epsilon).
Args |
|---|
x
|
Input tensor.
|
axis
|
The axis or axes along which to perform normalization.
Default to -1.
|
order
|
The exponent value in the norm formulation.
Defaults to 2.
|
Returns |
|---|
|
The normalized array.
|
Example:
x = keras.ops.convert_to_tensor([[1, 2, 3], [4, 5, 6]])
x_norm = keras.ops.math.normalize(x)
print(x_norm)
array([[0.26726124 0.5345225 0.8017837 ]
[0.45584232 0.5698029 0.68376344]], shape=(2, 3), dtype=float32)
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Last updated 2024-06-07 UTC.
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View source on GitHub